Grid-connected sustainable systems are increasingly susceptible to power quality (PQ) issues due to advancements in power electronics technology. Electric Vehicle Charging Stations (EVCS) experience significant distortions in two scenarios: (1) when connected to the grid, and (2) when operating independently on battery energy storage devices (BESD) and solar energy. Addressing these distortions is crucial for improving the system's Power Quality. To achieve this, a hybrid control approach is proposed, combining a Fractional Order Proportional Integral Controller (FOPIDC) for the shunt filter of the unified PQ conditioner (UPQC) with an Adaptive Neuro-Fuzzy Inference System (ANFIS). The primary goal of the UPQC is to maintain steady voltage across the DC capacitor (SVDC) during variations in load (such as EVCS, and non-linear balanced/unbalanced loads) and solar irradiation. Additional objectives include mitigating disturbances, voltage swell/sag, and grid voltage imbalances. The performance of the developed model is evaluated in both grid-connected and islanding scenarios across four distinct test cases. To demonstrate its effectiveness, the proposed system is compared to industry-standard controllers such as Sliding Mode Controllers (SMC) and Proportional Integral Controllers (PIC). While the methodology reduces THD to 2.40%, 2.23%, and 2.44%, it is slightly less effective than some existing methods highlighted in the literature.

Development of AI-Controller for Solar /Battery Fed H-Bridge Cascaded Multilevel Converter UPQC under Different Loading Conditions

Construct and Performance Investigation of a Hybrid ANFIS Controlled Islanded Micro-Grid